class_docstr: Selects the subgraph that corresponds to the
  largest connected components in the graph
  (functional name: :obj:`largest_connected_components`).
  
  Args:
      num_components (int, optional): Number of largest components to keep
          (default: :obj:`1`)
      connection (str, optional): Type of connection to use for directed
          graphs, can be either :obj:`'strong'` or :obj:`'weak'`.
          Nodes `i` and `j` are strongly connected if a path
          exists both from `i` to `j` and from `j` to `i`. A directed graph
          is weakly connected if replacing all of its directed edges with
          undirected edges produces a connected (undirected) graph.
          (default: :obj:`'weak'`)
code: def __repr__(self) -> str:
      return f"{self.__class__.__name__}({self.num_components})"
  
file_path: pytorch_geometric/torch_geometric/transforms/largest_connected_components.py
imports: import torch
  from torch_geometric.data import Data
  from torch_geometric.data.datapipes import functional_transform
  from torch_geometric.transforms import BaseTransform
  from torch_geometric.utils import to_scipy_sparse_matrix
label_desc: Use image node_id 3 for calling the LargestConnectedComponents obj's underlying member method code with example usage: obj.__repr__() and returns: self, str, self, str